Plasma Internal Inductance in the Presence of External Resonant Fields in IR-T1 Tokamak

In this paper we presented experimental investigation of effects of local limiter biasing (V_biasing = +200 v, V_biasing = +320 v) on the plasma parameters as plasma current, loop voltage, poloidal beta, plasma pressure, plasma energy, plasma resistance, plasma temperature, plasma displacement, Shafranov parameter and plasma internal inductance in IR-T1 tokamak. For these purposes, array of magnetic probes and also a diamagnetic loop have been used. The results show that applied biased voltage V_biasing = +200 v causes to decrease of about 40 % in plasma internal inductance. The plasma resistance and the plasma displacement have been decreased by V_biasing = +200 v. The main result of the application of V_biasing = +200 v is flatting the plasma parameters profiles. In other words, the addition of biasing voltage V_biasing = +200 v to plasma could be effective for improving the quality of tokamak plasma discharge by creating the steady state plasma. The plasma current, plasma pressure, plasma energy, plasma temperature and shift parameter have increased after the application of limiter biasing with V_biasing = +320 v but they decrease rapidly.     

Modified Cuckoo Optimization Algorithm (MCOA) to solve Precedence Constrained Sequencing Problem (PCSP)

In recent years, new meta-heuristic algorithms have been developed to solve optimization problems. Recently-introduced Cuckoo Optimization Algorithm (COA) has proven its excellent performance to solve different optimization problems. Precedence Constrained Sequencing Problem (PCSP) is related to locating the optimal sequence with the shortest traveling time among all feasible sequences. The problem is motivated by applications in networks, scheduling, project management, logistics, assembly flow and routing. Regarding numerous practical applications of PCSP, it can be asserted that PCSP is a useful tool for a variety of industrial planning and scheduling problems. However it can also be seen that the most approaches may not solve various types of PCSPs and in related papers considering definite conditions, a model is determined and solved. In this paper a new approach is presented for solving various types of PCSPs based on COA. Since COA at first was introduced to solve continuous optimization problems, in order to demonstrate the application of COA to find the optimal sequence of the PCSP, some proposed schemes have been applied in this paper with modifications in operators of the basic COA. In fact due to the discrete nature and characteristics of the PCSP, the basic COA should be modified to solve PSCPs. To evaluate the performance of the proposed algorithm, at first, an applied single machine scheduling problem from the literature that can be formulated as a PCSP and has optimal solution is described and solved. Then, several PCSP instances with different sizes from the literature that do not have optimal solutions are solved and results are compared to the algorithms of the literature. Computational results show that the proposed algorithm has better performance compared to presented well-known meta-heuristic algorithms presented to solve various types of PCSPs so far.     

Comparison and evaluation of dust detection algorithms using MODIS Aqua/Terra Level 1B data and MODIS/OMI dust products in the Middle East

Dust storms have a major impact on air quality, economic loss, and human health over large regions of the Middle East. Because of the broad extent of dust storms and also political–security issues in this region, satellite data are an important source of dust detection and mapping. The aim of this study was to compare and evaluate the performance of five main dust detection algorithms, including Ackerman, Miller, normalized difference dust index (NDDI), Roskovensky and Liou, and thermal-infrared dust index (TDI), using MODIS Level 1B and also MODIS Deep Blue AOD and OMI AI products in two dust events originating from Iraq and Saudi Arabia. Overall, results showed that the performance of the algorithms varied from event to event and it was not possible to use the published dust/no-dust thresholds for the algorithms tested in the study area. The MODIS AOD and OMI AI products were very effective for initial dust detection and the AOD and AI images correlated highly with the dust images at provincial scale (p-value <0.001), but the application of these products was limited at local scale due to their poor spatial resolution. Results also indicated that algorithms based on MODIS thermal infrared (TIR) bands or a combination of TIR and reflectance bands were better indicators of dust than reflectance-based ones. Among the TIR- based algorithms, TDI performed the best over water surfaces and dust sources, and accounted for approximately 93% and 90% of variations in the AOD and OMI AI data.     

Low-cost optical approach for noncontact predicting moisture content of apple slices during hot air drying

Absorption and scattering properties of product change as moisture content is reduced, but it has not been investigated how these changes are correlated. This study was aimed to measure and test the feasibility of using optical properties in predicting the moisture content of sliced apple samples during hot air drying. In this investigation, the noninvasive backscattering laser imaging technique at three wavelengths (650, 780, and 880?nm) and Farrell’s diffusion theory were used to determine absorption and reduced scattering coefficients. Artificial neural network model was applied to correlate the optical coefficients and moisture content of samples. The highest correlation between above-mentioned parameters was found at 780?nm. The best moisture content prediction result was obtained when absorption and reduced scattering coefficients were combined at three wavelengths with R_p?=?0.984. The results suggested that this method can be effectively used to predict the moisture content and control the drying process.     

Computational and Experimental Investigation of Immobilization of CuI Nanoparticles on 3-Aminopyridine Modified Poly(styrene-<Emphasis Type="Italic">co</Emphasis>-maleic anhydride) and Its Catalytic Application in Regioselective Synthesis of 1,2,3-Triazoles

Cu(I) nanoparticles (NPs) on modified poly(styrene-co-maleic anhydride) was prepared via a facile procedure. In this regard the modified co-polymer (SMA) was initially synthesized from the reaction of poly(styrene-co-maleic anhydride) with 3-aminopyridine. Upon the treatment of CuI with SMA, Cu(I) NPs were immobilized on SMA. This immobilized Cu(I) NPs was fully characterized by FTIR, SEM and EDAX analysis methods. Moreover, the interaction of Cu cations with 3-aminopyridine modified SMI catalyst via density functional theory (DFT) and quantum theory of atoms in molecules (QTAIM) computationally was studied. Our calculated results demonstrated that among 2,3 and 4 substituted aminopyridines for the modification of SMA, the 3-amnopyridine has the weakest ligand and Cu(I) interaction. However, the SMI image showed a suitable size of nanoparticles and inductively coupled plasma (ICP) analysis showed a higher Cu content in comparison with those of 2 and 4-substituted pyridines. The catalytic activity and reusability of this nanocatalyst system of 3-substituded aminopyridines was examined in the Huisgen 1,3-dipolar cycloaddition via click reaction. The reactions proceeded smoothly leading to regioselective synthesis of 1,4-disubstitued 1,2,4-triazole derivatives in excellent yields under mild reaction conditions. This heterogeneous catalytic system was separated easily by simple filtration and was reused without pre-activation at least in five runs without appreciable loss in its activity.     

Fuzzy community detection on the basis of similarities in structural/attribute in large-scale social networks

Artificial Intelligence Review - Community detection aims to partition a set of nodes with more similarities in the set than out of it based on different criteria like neighborhood similarity or...     

Evaluation of aflatoxin decontaminating by two strains of Saccharomyces cerevisiae and Lactobacillus rhamnosus strain GG in pistachio nuts

In this study, the surface binding ability of Saccharomayces cerevisiae and Lactobacillus rhamnosus GG (LBGG) to aflatoxin in pistachio nuts was compared. Results showed that Saccharomayces cerevisiae and Lactobacillus rhamnosus strains had aflatoxin binding ability of 40% and 35% with initial concentration of 10 ppb and 70% and 60% with initial concentration of 20 ppb aflatoxin, respectively. Acid treatment increased this ability for yeast and bacterium to 60% and 85% in first concentration and 73% and 90% for second concentration of aflatoxin, respectively. Also, heat treatment could raise surface binding of yeast to 55% and 75% for two concentrations. In addition, heat condition for Lactobacillus improved binding to 85% and 90% for two concentrations of aflatoxin. Experiments showed that microorganism’s immobilisation on contaminated pistachio had no effect on qualitative characteristics of pistachio such as colour, texture and peroxide value.     

Aflatoxin B1 degradation by Bacillus subtilis UTBSP1 isolated from pistachio nuts of Iran

Pistachio nuts are among the commodities with the highest risk of aflatoxin contamination in Iran. Aflatoxin B1 (AFB1) is one of the most hazardous mycotoxins for humans and livestock. In nature, there are microorganisms which are capable of reducing aflatoxins contamination in food and feed products. In this study, Bacillus subtilis strain UTBSP1 was isolated from pistachio nuts and studied for the degradation of AFB1. The AFB1 contents were determined by the use of HPTLC and HPLC as well as multiple reactions monitoring (MRM) method in LC-MS/MS. The results indicated B. subtilis UTBSP1 could considerably remediate AFB1 from nutrient broth culture and pistachio nut by 85.66% and 95%, respectively. Cell free supernatant fluid caused an apparent 78.39% decrease in AFB1 content. The optimal conditions for AFB1 degradation by cell free supernatant appeared at 35-40 °C, during 24 h. Furthermore, the results indicated that AFB1 degradation is enzymatic and responsible enzymes are extracellular and constitutively produced. The destructive AFB1 differed from standard AFB1 chemically, and lost a fluorescence property.